1. The Quick Sort Textbook Authors: Ken Lambert & Doug Nance PowerPoint Lecture by Dave Clausen

2. Mr. Dave Clausen2 Quick Sort Description One of the fastest sorting techniques available is the quick sort. Like binary search, this method uses a recursive, divide and conquer strategy. The basic idea is to separate a list of items into two parts, surrounding a distinguished item called the pivot. At the end of the process, one part will contain items smaller than the pivot and the other part will contain items larger than the pivot.

3. Mr. Dave Clausen3 Quick Sort Trace If an unsorted list (represented as vector a ) originally contains: we might select the item in the middle position, a[5], as the pivot, which is 8 in our illustration. Our process would then put all values less than 8 on the left side and all values greater than 8 on the right side. This first subdivision produces Now, each sublist is subdivided in exactly the same manner. This process continues until all sublists are in order. The list is then sorted. This is a recursive process.

4. Mr. Dave Clausen4 Quick Sort Trace 2 We choose the value in the middle for the pivot. As in binary search, the index of this value is found by (first + last) / 2, –where first and last are the indices of the initial and final items in the vector representing the list. –We then identify a left_arrow and right_arrow on the far left and far right, respectively. –This can be envisioned as: – where left_arrow and right_arrow initially represent the lowest and highest indices of the vector items.

5. Mr. Dave Clausen5 Quick Sort Trace 3 Starting on the right, the right_arrow is moved left until a value less than or equal to the pivot is encountered. This produces In a similar manner, left_arrow is moved right until a value greater than or equal to the pivot is encountered. This is the situation just encountered. Now the contents of the two vector items are swapped to produce

6. Mr. Dave Clausen6 Quick Sort Trace 4 We continue by moving right_arrow left to produce and moving left_arrow right yields These values are exchanged to produce

7. Mr. Dave Clausen7 Quick Sort Trace 5 This process stops when left_arrow > right_arrow is TRUE. Since this is still FALSE at this point, the next right_arrow move produces and the left_arrow move to the right yields

8. Mr. Dave Clausen8 Quick Sort Trace 6 Because we are looking for a value greater than or equal to pivot when moving left, left_arrow stops moving and an exchange is made to produce Notice that the pivot, 8, has been exchanged to occupy a new position. This is acceptable because pivot is the value of the item, not the index. As before, right_arrow is moved left and left_arrow is moved right to produce

9. Mr. Dave Clausen9 Quick Sort Trace 7 Since right_arrow < left_arrow is TRUE, the first subdivision is complete. At this stage, numbers smaller than pivot are on the left side and numbers larger than pivot are on the right side. This produces two sublists that can be envisioned as Each sublist can now be sorted by the same function. This would require a recursive call to the sorting function. In each case, the vector is passed as a parameter together with the right and left indices for the appropriate sublist.

10. Mr. Dave Clausen10 void QuickSort(apvector &list, int left, int right) { int pivot, leftArrow, rightArrow; leftArrow = left; rightArrow = right; pivot = list[(left + right) / 2]; do { while (list[rightArrow] > pivot) --rightArrow; while (list[leftArrow] < pivot) ++leftArrow; if (leftArrow <= rightArrow) { Swap_Data(list[leftArrow], list[rightArrow]); ++leftArrow; --rightArrow; } } while (rightArrow >= leftArrow); if (left < rightArrow) QuickSort(list, left, rightArrow); if (leftArrow < right) QuickSort(list, leftArrow, right); } Quick Sort Source Code C ++

11. Mr. Dave Clausen11 Quick Sort Interface Code C++ For many of the recursive functions it is customary to start with an “interface” function, since recursive functions call themselves. Here is the “interface” for the Quick Sort (this function is called first, which in turn calls the recursive function QuickSort) void Q_Sort(apvector &list) { QuickSort(list, 0, list.length() - 1); } You can use logical size - 1 instead of list.length() –1 if the logical and physical sizes are not the same. Don’t forget to pass logical size to the Q_Sort function.

12. Mr. Dave Clausen12 Quick Sort uses Swap Data Quick Sort uses the same helper function called Swap Data that the Bubble Sort and Selection Sort used. The source code can be found on the next slide for your convenience.

13. Mr. Dave Clausen13 Swap Data Source Code C++ void Swap_Data (int &number1, int &number2) { int temp; temp = number1; number1 = number2; number2 = temp; }

14. Mr. Dave Clausen14 Big - O Notation Big - O notation is used to describe the efficiency of a search or sort. The actual time necessary to complete the sort varies according to the speed of your system. Big - O notation is an approximate mathematical formula to determine how many operations are necessary to perform the search or sort. The Big - O notation for the Quick Sort is O(nlog 2 n), because it takes approximately nlog 2 n passes to find the target element.